There are situations where it is necessary to remotely measure relative position and orientation of an object using imagery of the object acquired remotely using optical, radar, passive microwave, or other sensors capable of providing data from which images may be generated. Such imagery may be conventional images, as may be generated by a conventional video camera using ambient light or flash photography, or other types of images generated from data produced by active, semi-active, or passive sensors, and may include, for example, synthetic aperture radar images, or inverse synthetic aperture radar images, or other images produced from radar data, or infrared images produced by a passive IR sensor.
A specific problem that led to development of the instant invention is measurement of position and orientation of one aircraft relative to another for purposes of flying an unmanned aerial vehicle in formation, such as formations supporting aerial refueling. However, the instant invention has much broader applications, including applications in determining object orientation to support autonomous, robotic servicing of satellites, robotic grasping and manipulating of objects in assembly lines, or other automated production or maintenance operations.
One method for remote measurement or estimation of object orientation involves use of a matched filter correlator, such as described by VanderLugt, with an extensive library of matched filters for different reference object orientations, in a practical system implementation such as described by Hartman and Farr in U.S. patent application Ser. No. 10/831,587. In a method disclosed earlier, orientation of an object relative to a position of an image-producing sensor may be determined by using a succession of matched filter correlations with an image of an object using reference filters generated for different viewing angles and ranges of a reference object. Such reference filters may be generated in sets at several ranges from a reference object, with each set including reference filters generated, for example, at 5, 1, or 0.5 degree increments in each of roll, pitch, and yaw, depending upon object complexity and desired resolution of angular measurement of object orientation. Ranges for reference filter sets may be selected, for example, at intervals where scale size of a target image changes by 10 percent. In this method, a correlation producing a highest correlation peak using a reference filter for a given range and orientation (i.e., combination of roll, pitch, and yaw) may be taken as a best estimate of object orientation. In this method, interpolation between correlations using adjacent reference filters (i.e., those nearest in roll, pitch, or yaw to a reference filter producing a highest correlation peak) may be used to further refine an estimate of object orientation. An undesirable requirement of this method, however, is that it may be necessary to generate and store a large number of reference filters, and make a significant number of comparisons using multiple reference filters in order to measure orientation of an object down to accuracies of a degree or so in roll, pitch, and/or yaw, or to obtain range accuracies of a few percent of range. This may impose undesirable storage and processing burdens, particularly on real-time systems, such as may be used in automated guidance systems.
The instant invention provides a method for measuring object orientation that requires far fewer reference filters and fewer correlations, at time of measurement of orientation of an object of unknown orientation, to obtain similar accuracy and precision in measuring object orientation. These innovations offer significant advantages for real-time applications where orientation of an object must be rapidly determined from remote observations, but may also be beneficial in other applications as well. In this application, “orientation,” “aspect,” “pose,” and “attitude” have the same meaning with reference to an object's orientation with respect to a point from which an observation is taken.